Defining a Random Sample in Research

Defining a Random Sample in Research Student Resources Study Guides and Tips Print Random Samples in Research Studies How Subsets of Subjects Are Used for Research By Kendra Cherry facebook twitter Kendra Cherry, MS, is an author, educational consultant, and speaker focused on helping students learn about psychology. Learn about our editorial policy Kendra Cherry Updated on January 09, 2020 Matt Lincoln / Cultura / Getty Images More in Student Resources Study Guides and Tips APA Style and Writing Careers The term random sample comes up a lot when youre reading about medical research. Understanding this term can help you interpret those health studies you come across in the news and get a better grasp of how they may, or may not, apply to you. Simply put, a random sample is a subset of individuals randomly selected by researchers to represent an entire group as a whole. The goal is to get a sample of people that is representative of the larger population. For example, if researchers were interested in learning about  alcoholic use  among college students in the United States, the larger population (in other words, the group of interest), would be made up of every kid in every college and university in the country. It would be virtually impossible to interview each and every one of these people to find out if they drink, what types of alcohol they drink, how often, under what circumstances, how much (a beer or two per week versus enough to get intoxicated every weekend), and so forth. Instead of undertaking such a gargantuan task, scientists will pull together a random sample of college students to represent the total population of college students. How Researchers Create Random Samples Random sampling can be costly and time-consuming. However, this approach to gathering data for research does provide the best chance of putting together an unbiased sample that is truly representative of an entire group as a whole. Going back to the imaginary study of alcohol use among college students, heres how random sampling might work. According to the National Center for Education Statistics ( NCES), approximately 20.2 million students were enrolled in U.S. colleges and universities in 2015, the most recent statistics available. These 20 million-plus individuals represent the total population to be studied. For the purpose of drawing a random sample of this group, all students must have an equal chance of being selected. For example, scientists conducting the study would need to make sure that the sample included the same percentage of men and women as the larger population. According to the NCES  statistics, 11.5 million of the total population of college students are female and 8.7 million are male. The sample group would need to reflect this same ratio of women to men. Besides gender, researchers would also want to go through the same process for other characteristicsâ€"for example, race, cultural background, year in school, socio-economic status, and so forth, depending on the specific purpose of the study. For instance, if they wanted to home in on alcohol use among Asian students, they would create a random sample consisting only of Asian students. By the same token, if the study was focused on how much students drink during the week, they would create a questionnaire or other method for finding only kids who drink on weekdays for their research. When you read a health study based on a random sample, be aware that the findings are based not on every single person in the population that fit certain criteria, but on a subset of subjects chosen to represent them. This should help you put the study in perspective.